DOI QR코드

DOI QR Code

2×3 이중 설계에서 생물학적 동등성 평가

Assessing bioequivalence in 2×3 dual designs

  • 우화형 (중앙대학교 응용통계학과) ;
  • 정규진 (한남대학교 비즈니스통계학과) ;
  • 박상규 (중앙대학교 응용통계학과)
  • Woo, Hwa Hyoung (Department of Applied Statistics, Chung-Ang University) ;
  • Jeong, Gyu Jin (Department of Business Statistics, Han Nam University) ;
  • Park, Sang-Gue (Department of Applied Statistics, Chung-Ang University)
  • 투고 : 2017.06.08
  • 심사 : 2017.07.08
  • 발행 : 2017.07.31

초록

두 제제의 생체이용률을 비교하여 동등성을 입증하는 생물학적 동등성 시험은 표준 $2{\times}2$ 교차설계를 원칙으로 하고 있으나, 최근에는 제제의 특성이 고변동성으로 인해 표준 $2{\times}2$ 교차설계를 사용할 경우 지나치게 많은 피험자가 필요하게 되면서, EMA나 MFDS 등에서는 $2{\times}2$ 교차설계를 확장한 $2{\times}4$, $4{\times}2$ 또는 $4{\times}4$ 등의 고차원 설계를 권장하고 있다. $2{\times}3$ 교차설계는 표준 $2{\times}2$ 교차설계에서 1기간을 확장한 설계로 불균형 설계이기는 하지만 $2{\times}4$ 교차설계와 비교해서 경제적, 윤리적 측면에서 장점을 갖고 있는 설계라 할 수 있다. 본 연구에서는 $2{\times}3$ 이중설계를 활용하는 생물학적 동등성 시험에서 설계의 통계적 특성을 고찰해 보고, 생물학적 동등성 평가를 위한 통계적 설계 및 추론 절차를 새롭게 개정된 의약품동등성시험기준을 적용하여 논의한다.

Assessing bioequivalence between original drug and generic drug is traditionally based on $2{\times}2$ crossover design. As bioequivalence trials for highly variable drugs are getting popular, the required sample size based on $2{\times}2$ crossover design would be very large, which might cause the ethical concerns. Regulatory agencies like EMA and MFDS recommended higher order crossover designs such as $2{\times}4$, $4{\times}2$ and $4{\times}4$ crossover designs. Alternatively, a $2{\times}3$ dual design may be recommended in terms of economical and ethical points of view in comparison with the $2{\times}4$ crossover design for highly variable drug. In this study, we consider some statistical characteristics of $2{\times}3$ dual design and propose statistical procedures for calculating sample size and assessing bioequivalence based on $2{\times}3$ dual design. We also discuss the proposed procedures from the perspective of newly revised bioequivalence guidance issued by MFDS.

키워드

참고문헌

  1. Chow, S. C. and Liu, L. (2008). Design and analysis of bioavailability and bioequivalence studies, Chapman & Hall.
  2. Chow, S. C., Shao, J. and Wang, H. (2002). Individual bioequivalence testing under $2{\times}3$ designs. Statistics in Medicine, 21, 629-648. https://doi.org/10.1002/sim.1056
  3. Chow, S. C. and Wang, H. (2001). On sample size calculation in bioequivalence trials. Journal of Pharmacokinetics and Pharmacodynamics, 28, 155-169. https://doi.org/10.1023/A:1011503032353
  4. EMA (2010). MEA guideline on the investigation of bioequivalence, CPMP/EWP/QWP/1401/98 Rev.1/Corr, London.
  5. Jeong, G. and Park, S. (2011). On evaluation of bioequivalence for highly variable drugs. Korean Journal of Applied Statistics, 24, 1055-1076. https://doi.org/10.5351/KJAS.2011.24.6.1055
  6. Kershner R. P. and Federer, W. T. (1981). Two-treatment crossover designs for estimating a variety of effects. Journal of the American Statistical Association, 76, 612-618. https://doi.org/10.1080/01621459.1981.10477693
  7. Noh, S. and Park, S. (2013). Some statistical consideration on $2{\times}k$ crossover designs for bioequivalence trial. Korean Journal of Applied Statistics, 26, 675-686. https://doi.org/10.5351/KJAS.2013.26.4.675
  8. Park, J. and Park, S. (2016). Assessing bioequivalence for highly variable drugs based on $3{\times}3$ crossover designs. Korean Journal of Applied Statistics, 29, 279-289. https://doi.org/10.5351/KJAS.2016.29.2.279
  9. Park, S. (2007). On sample size determination of bioequivalence trials. Journal of Korean Data & Information Science Society, 18, 365-373.
  10. Woo, H. and Park, S. (2014). Statistical procedures of add-on trials for bioequivalence in $2{\times}k$ crossover designs. Journal of Korean Data & Information Science Society, 25, 1181-1193. https://doi.org/10.7465/jkdi.2014.25.6.1181